dirch_from_allocations: Given a vector of different categories in 1...n and a prior,...
In benmoran11/rubias: Bayesian Inference from the Conditional Genetic Stock Identification Model
dirch_from_allocations R Documentation
Given a vector of different categories in 1...n and a prior,
simulate a Dirichlet random vector
Description
Takes a vector of collection indices to which individuals (vector elements) were assigned,
and returns a Dirichlet random variable generated by adding the prior to the sum
of each collection's occurrences, and simulating an alpha from a gamma distribution
with this shape parameter.
Usage
dirch_from_allocations(C, lambda)
Arguments
C
a vector giving different categories of individual
(not counts of categories - untabulated)
lambda
priors for the categories
Details
The categories are labeled in C from 1 up to n. n is the length of lambda,
which is a vector of priors. Note that all elements of lambda
must be strictly greater than 0.
benmoran11/rubias documentation built on Feb. 1, 2024, 10:52 p.m.
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| dirch_from_allocations | R Documentation |
Given a vector of different categories in 1...n and a prior, simulate a Dirichlet random vector
Description
Takes a vector of collection indices to which individuals (vector elements) were assigned, and returns a Dirichlet random variable generated by adding the prior to the sum of each collection's occurrences, and simulating an alpha from a gamma distribution with this shape parameter.
Usage
dirch_from_allocations(C, lambda)
Arguments
C |
a vector giving different categories of individual (not counts of categories - untabulated) |
lambda |
priors for the categories |
Details
The categories are labeled in C from 1 up to n. n is the length of lambda,
which is a vector of priors. Note that all elements of lambda
must be strictly greater than 0.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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